Stochastic mesoscale circulation dynamics in the thermal ocean

TL;DR

This paper develops stochastic models for mesoscale ocean circulation influenced by buoyancy gradients, extending deterministic models with stochastic transport to better capture small-scale, high-wavenumber instabilities and their impact on fluid transport.

Contribution

It introduces a stochastic transport framework for the TRSW, TL1, and TQG models using SALT, providing a new approach to model small-scale instabilities in stratified ocean flows.

Findings

Stochastic models capture small-scale circulation effects.

High-wavenumber instabilities influence fluid transport.

Framework facilitates uncertainty quantification and data assimilation.

Abstract

In analogy with similar effects in adiabatic compressible fluid dynamics, the effects of buoyancy gradients on incompressible stratified flows are said to be `thermal'. The thermal rotating shallow water (TRSW) model equations contain three small nondimensional parameters. These are the Rossby number, the Froude number and the buoyancy parameter. Asymptotic expansion of the TRSW model equations in these three small parameters leads to the deterministic thermal versions of the Salmon's L1 (TL1) model and the thermal quasi-geostrophic (TQG) model, upon expanding in the neighbourhood of thermal quasi-geostrophic balance among the flow velocity and the gradients of free surface elevation and buoyancy. The linear instability of TQG at high wave number tends to create circulation at small scales. Such a high wave number instability could be unresolvable in many computational simulations, but its presence at small scales may contribute significantly to fluid transport at resolvable scales. Sometimes such effects are modelled via `stochastic backscatter of kinetic energy'. Here we try another approach. Namely, we model `stochastic transport' in the hierarchy of models TRSW/TL1/TQG. The models are derived via the approach of stochastic advection by Lie transport (SALT) as obtained from a recently introduced stochastic version of the Euler--Poincar\'e variational principle. We also indicate the potential next steps for applying these models in uncertainty quantification and data assimilation of the rapid, high wavenumber effects of buoyancy fronts at these three levels of description by using the data-driven stochastic parametrisation algorithms derived previously using the SALT approach.